Guide Optimal design of experiments : a case study approach

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The objective of the Sampling Theory section of the module is to introduce several different methods for obtaining samples from finite populations.

Description

Experiments which aim to discover improved conditions are commonplace in industry, agriculture, etc. The purpose of experimental design is to maximise the information on what is of interest with the minimum use of resources.

Module 7: Experimental Design

The aim of the Design section is to introduce some of the more important design concepts. Exam format: all questions compulsory.


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Experimental Design A review of linear models: matrix notation; least squares estimation; orthogonality; prediction; confidence regions. Optimality criteria: D-optimal, G-optimal, V-optimal and A-optimal designs.

Outline syllabus

Completely randomised designs and randomised block designs. Latin squares and balanced incomplete block designs.

Factorial designs: complete factorial designs; fractional factorial designs; screening experiments. If you would like to read more about this check out the Privacy Policy page. Important Message.

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Design of experiments (DOE) - Introduction

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